A New Clustering Methodology for the Analysis of Sorted or Categorized Stimuli
Desarbo, Wayne S.; Jedidi, Kamel; Johnson, Michael D.
This paper introduces a new stochastic clustering methodology devised for the analysis of categorized or sorted data. The methodology reveals consumers' common category knowledge as well as individual differences in using this knowledge for classifying brands in a designated product class. A small study involving the categorization of 28 brands of U.S. automobiles is presented where the results of the proposed methodology are compared with those obtained from KMEANS clustering. Finally, directions for future research are discussed.
cluster analysis; categorization; sorting tasks; maximum likelihood estimation
Required Publisher Statement: © Springer. Final version published as: Desarbo, W. S., Jedidi, K., & Johnson, M. D. (1991). A new clustering methodology for the analysis of sorted or categorized stimuli. Marketing Letters, 2(3), 267–279. Reprinted with permission. All rights reserved.